Common Mistakes in Data Visualization - Paul Barnhurst
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Common Mistakes in Data Visualization: 5 Tips on Helping Your Leaders Make Data-Driven Decisions

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You probably know him as “The FP&A Guy.” For nearly 15 years, Paul Barnhurst has been a leader, influencer and educator in the FP&A community.

Visualizations tell your audience a story for better or worse. No matter how great your analysis may be, your audience will remember mostly the graphics and story you use to present your analysis.

A poorly crafted story with weak visuals will destroy your credibility, and possibly even worse, mislead your audience. A well-crafted story with strong visuals goes a long way toward positively influencing your audience.

In this blog post, you’ll learn five tips on how not to mislead your audience. I’ll take you through common mistakes in data visualization to ensure your next presentation will not only tell a story, but also help your business leaders make informed, data-driven decisions.

1. Keep Visuals Simple and Easy To Understand

Common Mistakes in Data Visualization 1Source: LivingQlik

I stared at this visual for several minutes and I’m still not sure I understand what it’s trying to tell us. Talk about cognitive overload. I thought 3-D graphs were hard to follow, but this 4-D graph hurts my brain every time I look at it.

Keep your graphs simple and never use 3- or 4-D graphs. They’re hard for your audience to process.

2. Choose Color Wisely

Common Mistakes in Data Visualization 2Source: KCRA

This graph has a lot going wrong for it, from the color, to the labels, to the misleading message. We could spend this entire blog post discussing all the poor choices that led to this graph, but let’s focus on the color selection. When I shared this on LinkedIn, one of my followers commented, “The worst is the color. It looks like the more shootings the better 🤨.” The color choice for this graph makes no sense.

Color should only be used to help drive a point home—not simply because you can use color. Next time you decide to get creative with your color, ask yourself, “Will it benefit my audience?” If the answer is “no,” stick with gray.

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3. Don’t Invert Axes

Common Mistakes in Data Visualization 3Source: Buzzfeed News

With inverted axes, it suggests that the more an event happens, the less it looks like it’s happening. It’s confusing. The inverted axes of this graph leads the audience to believe that enacting the Florida “Stand Your Ground” law has resulted in fewer shootings, when in fact, that’s not true.

When working with your axes, start from zero. Don’t use them to tell the story you want the data to tell, but instead, tell the actual story.

4. Don’t Overwhelm Audiences With Numbers

Common Mistakes in Data Visualization 4Source: PolicyViz

Like overusing color in the earlier graph, this one overuses numerical labels. They failed to understand that, just because you can put a number somewhere, doesn’t mean you should. Graphs are designed to tell a story visually, so tell the story with the fewest numbers possible—without sacrificing storytelling accuracy.

In this graph, both the X and Y axes share the same scale and every data point is labeled. I would’ve labeled both axes with a meaningful description that helps the audience understand what the numbers represent. Put numbers along the axes only when they help visually tell the story, not because the underlying data merely has numbers associated with it.

5. Provide Enough Context for Decision Makers To Make a Decision

Common Mistakes in Data Visualization 5Source: Statistics How To

This graph lacks context. We see that the number of people receiving some form of federal welfare is increasing, but we can’t see if that number is increasing relative to the overall population. We’re not told either if the amount paid per person is increasing. This graph simply needs more information.

How do you lead your business leaders toward informed, data-driven decisions?

Data Visualization Helps Your Business Leaders Make Informed, Data-Driven Decisions

After looking at those five poorly designed graphs, it’s clear that these common mistakes in data visualization can quickly destroy your credibility and your hours of hard work. Your presentation of the data often is as, if not more, important than the data itself. Remember: Your visuals tell your audience a story for better or worse, and your audience will remember mostly the graphics and story, not the data.

Look at the visuals you’ve been designing lately and ask yourself, “Will this help my business leaders make an informed, data-driven decision?” If the answer is “no,” then your visual isn’t a well-crafted story and won’t positively influence your audience. Eliminate that graph or continue working on it—until it helps your business leaders make an informed, data-driven decision.

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